Speaker variability often affects the performance of a speech recognition system. For example, the performance of a speech recognition system developed using adult speech may degrade when testing on child speech. One major source of speaker variability is the vocal tract length of the speaker. The vocal tract length changes between different people (e.g. male, female, children) causing a change in the formant frequencies of the speech spectrum (e.g. higher for females and lower for males). Vocal Tract Length Normalization (VTLN) is a technique used to reduce the effects of speaker's vocal tract variability through frequency warping. Using VTLN algorithms in a real-world application (e.g., XBOX KINECT) with low or zero latency, however, can be challenging.